scholarly journals A phase-error prediction method for coherent beam combining via convolutional neural network

Optik ◽  
2021 ◽  
pp. 167827
Author(s):  
Haolong Jia ◽  
Jing Zuo ◽  
Qiliang Bao ◽  
Chao Geng ◽  
Xinyang Li ◽  
...  
Author(s):  
Tianyue Hou ◽  
Yi An ◽  
Qi Chang ◽  
Pengfei Ma ◽  
Jun Li ◽  
...  

We incorporate deep learning (DL) into tiled aperture coherent beam combining (CBC) systems for the first time, to the best of our knowledge. By using a well-trained convolutional neural network DL model, which has been constructed at a non-focal-plane to avoid the data collision problem, the relative phase of each beamlet could be accurately estimated, and then the phase error in the CBC system could be compensated directly by a servo phase control system. The feasibility and extensibility of the phase control method have been demonstrated by simulating the coherent combining of different hexagonal arrays. This DL-based phase control method offers a new way of eliminating dynamic phase noise in tiled aperture CBC systems, and it could provide a valuable reference on alleviating the long-standing problem that the phase control bandwidth decreases as the number of array elements increases.


CLEO: 2013 ◽  
2013 ◽  
Author(s):  
Hung-Sheng Chiang ◽  
James R. Leger ◽  
Johan Nilsson ◽  
Jayanta Sahu

2021 ◽  
Vol 140 ◽  
pp. 107016 ◽  
Author(s):  
Pengfei Ma ◽  
Hongxiang Chang ◽  
Yanxing Ma ◽  
Rongtao Su ◽  
Yunfeng Qi ◽  
...  

2017 ◽  
Vol 42 (19) ◽  
pp. 3960 ◽  
Author(s):  
Chun Peng ◽  
Xiaoyan Liang ◽  
Renqi Liu ◽  
Wenqi Li ◽  
Ruxin Li

Laser Physics ◽  
2010 ◽  
Vol 21 (1) ◽  
pp. 172-175 ◽  
Author(s):  
P. Zhou ◽  
X. L. Wang ◽  
Y. X. Ma ◽  
K. Han ◽  
Z. J. Liu

2011 ◽  
Vol 36 (4) ◽  
pp. 448 ◽  
Author(s):  
Henrik Tünnermann ◽  
Jörg Neumann ◽  
Dietmar Kracht ◽  
Peter Weßels

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